REPORT NFL kicking

Dataset statistics

Number of variables	31
Number of observations	1625
Missing cells	4
Missing cells (%)	< 0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.2 MiB
Average record size in memory	796.8 B

Variable types

Categorical	14
Numeric	16
Boolean	1

Alerts

`game_id` has a high cardinality: 820 distinct values	High cardinality
`player` has a high cardinality: 66 distinct values	High cardinality
`game_date` has a high cardinality: 174 distinct values	High cardinality
`fga` is highly correlated with `fgm` and 5 other fields	High correlation
`fgm` is highly correlated with `fga` and 5 other fields	High correlation
`xpa` is highly correlated with `xpm`	High correlation
`xpm` is highly correlated with `xpa`	High correlation
`fga_0_39` is highly correlated with `fga` and 5 other fields	High correlation
`fgm_0_39` is highly correlated with `fga` and 5 other fields	High correlation
`fga_40_49` is highly correlated with `fgm_40_49`	High correlation
`fgm_40_49` is highly correlated with `fga_40_49` and 3 other fields	High correlation
`fga_50` is highly correlated with `fgm_50`	High correlation
`fgm_50` is highly correlated with `fga_50`	High correlation
`Total_DKP` is highly correlated with `fga` and 6 other fields	High correlation
`Total_FDP` is highly correlated with `fga` and 6 other fields	High correlation
`Total_SDP` is highly correlated with `fga` and 6 other fields	High correlation
`fga` is highly correlated with `fgm` and 5 other fields	High correlation
`fgm` is highly correlated with `fga` and 5 other fields	High correlation
`xpa` is highly correlated with `xpm`	High correlation
`xpm` is highly correlated with `xpa`	High correlation
`fga_0_39` is highly correlated with `fga` and 5 other fields	High correlation
`fgm_0_39` is highly correlated with `fga` and 5 other fields	High correlation
`fga_40_49` is highly correlated with `fgm_40_49`	High correlation
`fgm_40_49` is highly correlated with `fga_40_49` and 3 other fields	High correlation
`fga_50` is highly correlated with `fgm_50`	High correlation
`fgm_50` is highly correlated with `fga_50`	High correlation
`Total_DKP` is highly correlated with `fga` and 6 other fields	High correlation
`Total_FDP` is highly correlated with `fga` and 6 other fields	High correlation
`Total_SDP` is highly correlated with `fga` and 6 other fields	High correlation
`fga` is highly correlated with `fgm` and 4 other fields	High correlation
`fgm` is highly correlated with `fga` and 5 other fields	High correlation
`xpa` is highly correlated with `xpm`	High correlation
`xpm` is highly correlated with `xpa`	High correlation
`fga_0_39` is highly correlated with `fga` and 2 other fields	High correlation
`fgm_0_39` is highly correlated with `fgm` and 1 other fields	High correlation
`fga_40_49` is highly correlated with `fgm_40_49`	High correlation
`fgm_40_49` is highly correlated with `fga_40_49`	High correlation
`fga_50` is highly correlated with `fgm_50`	High correlation
`fgm_50` is highly correlated with `fga_50`	High correlation
`Total_DKP` is highly correlated with `fga` and 3 other fields	High correlation
`Total_FDP` is highly correlated with `fga` and 3 other fields	High correlation
`Total_SDP` is highly correlated with `fga` and 3 other fields	High correlation
`home_team` is highly correlated with `Vegas_Favorite` and 2 other fields	High correlation
`player` is highly correlated with `Off_abbrev`	High correlation
`Vegas_Favorite` is highly correlated with `home_team`	High correlation
`fga_50` is highly correlated with `fgm_50`	High correlation
`Surface` is highly correlated with `home_team`	High correlation
`Roof` is highly correlated with `home_team`	High correlation
`fgm_50` is highly correlated with `fga_50`	High correlation
`fga_40_49` is highly correlated with `fgm_40_49`	High correlation
`Off_abbrev` is highly correlated with `player`	High correlation
`fgm_40_49` is highly correlated with `fga_40_49`	High correlation
`Off_abbrev` is highly correlated with `Def_abbrev` and 8 other fields	High correlation
`Def_abbrev` is highly correlated with `Off_abbrev` and 8 other fields	High correlation
`fga` is highly correlated with `Off_abbrev` and 8 other fields	High correlation
`fgm` is highly correlated with `Off_abbrev` and 9 other fields	High correlation
`xpa` is highly correlated with `xpm` and 2 other fields	High correlation
`xpm` is highly correlated with `xpa` and 2 other fields	High correlation
`fga_0_39` is highly correlated with `fga` and 5 other fields	High correlation
`fgm_0_39` is highly correlated with `fga` and 5 other fields	High correlation
`fga_40_49` is highly correlated with `fga` and 4 other fields	High correlation
`fgm_40_49` is highly correlated with `fgm` and 4 other fields	High correlation
`fga_50` is highly correlated with `fgm_50`	High correlation
`fgm_50` is highly correlated with `fgm` and 4 other fields	High correlation
`player` is highly correlated with `Off_abbrev` and 6 other fields	High correlation
`Total_DKP` is highly correlated with `fga` and 8 other fields	High correlation
`Total_FDP` is highly correlated with `fga` and 8 other fields	High correlation
`Total_SDP` is highly correlated with `fga` and 8 other fields	High correlation
`vis_team` is highly correlated with `Off_abbrev` and 4 other fields	High correlation
`home_team` is highly correlated with `Off_abbrev` and 10 other fields	High correlation
`vis_score` is highly correlated with `xpa` and 1 other fields	High correlation
`home_score` is highly correlated with `xpa` and 1 other fields	High correlation
`Roof` is highly correlated with `Off_abbrev` and 8 other fields	High correlation
`Surface` is highly correlated with `Off_abbrev` and 5 other fields	High correlation
`Temperature` is highly correlated with `home_team` and 4 other fields	High correlation
`Humidity` is highly correlated with `home_team` and 3 other fields	High correlation
`Wind_Speed` is highly correlated with `home_team` and 3 other fields	High correlation
`Vegas_Favorite` is highly correlated with `Off_abbrev` and 10 other fields	High correlation
`Over_Under` is highly correlated with `home_team` and 1 other fields	High correlation
`game_id` is uniformly distributed	Uniform
`vis_team` is uniformly distributed	Uniform
`home_team` is uniformly distributed	Uniform
`fga` has 231 (14.2%) zeros	Zeros
`fgm` has 285 (17.5%) zeros	Zeros
`xpa` has 143 (8.8%) zeros	Zeros
`xpm` has 178 (11.0%) zeros	Zeros
`fga_0_39` has 649 (39.9%) zeros	Zeros
`fgm_0_39` has 678 (41.7%) zeros	Zeros
`Total_DKP` has 29 (1.8%) zeros	Zeros
`Total_FDP` has 29 (1.8%) zeros	Zeros
`Total_SDP` has 29 (1.8%) zeros	Zeros
`Wind_Speed` has 589 (36.2%) zeros	Zeros

Reproduction

Analysis started	2022-09-02 02:18:17.379968
Analysis finished	2022-09-02 02:19:24.022107
Duration	1 minute and 6.64 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

game_id
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	820
Distinct (%)	50.5%
Missing	0
Missing (%)	0.0%
Memory size	109.6 KiB

202110100tam	3
202012270nyj	3
202109120nwe	2
202102070tam	2
202109090tam	2
Other values (815)	1613

Length

Max length	12
Median length	12
Mean length	12
Min length	12

Characters and Unicode

Total characters	19500
Distinct characters	34
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17 ?
Unique (%)	1.0%

Sample

1st row	201909050chi
2nd row	201909050chi
3rd row	201909080car
4th row	201909080car
5th row	201909080cle

Common Values

Value	Count	Frequency (%)
202110100tam	3	0.2%
202012270nyj	3	0.2%
202109120nwe	2	0.1%
202102070tam	2	0.1%
202109090tam	2	0.1%
202109120atl	2	0.1%
202109120buf	2	0.1%
202109120cin	2	0.1%
202109120clt	2	0.1%
202109120det	2	0.1%
Other values (810)	1603	98.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
202110100tam	3	0.2%
202012270nyj	3	0.2%
201909080nwe	2	0.1%
201909290buf	2	0.1%
201909150ram	2	0.1%
201909150rai	2	0.1%
201909150pit	2	0.1%
201909150oti	2	0.1%
201909080cle	2	0.1%
201909080crd	2	0.1%
Other values (810)	1603	98.6%

Most occurring characters

Value	Count	Frequency (%)
0	5230	26.8%
2	4006	20.5%
1	3402	17.4%
9	1013	5.2%
a	615	3.2%
n	471	2.4%
i	400	2.1%
t	357	1.8%
r	302	1.5%
c	296	1.5%
Other values (24)	3408	17.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	14625	75.0%
Lowercase Letter	4875	25.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	615	12.6%
n	471	9.7%
i	400	8.2%
t	357	7.3%
r	302	6.2%
c	296	6.1%
e	248	5.1%
d	243	5.0%
m	202	4.1%
s	201	4.1%
Other values (14)	1540	31.6%

Decimal Number

Value	Count	Frequency (%)
0	5230	35.8%
2	4006	27.4%
1	3402	23.3%
9	1013	6.9%
3	224	1.5%
7	176	1.2%
5	161	1.1%
8	154	1.1%
6	137	0.9%
4	122	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	14625	75.0%
Latin	4875	25.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	615	12.6%
n	471	9.7%
i	400	8.2%
t	357	7.3%
r	302	6.2%
c	296	6.1%
e	248	5.1%
d	243	5.0%
m	202	4.1%
s	201	4.1%
Other values (14)	1540	31.6%

Common

Value	Count	Frequency (%)
0	5230	35.8%
2	4006	27.4%
1	3402	23.3%
9	1013	6.9%
3	224	1.5%
7	176	1.2%
5	161	1.1%
8	154	1.1%
6	137	0.9%
4	122	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	19500	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	5230	26.8%
2	4006	20.5%
1	3402	17.4%
9	1013	5.2%
a	615	3.2%
n	471	2.4%
i	400	2.1%
t	357	1.8%
r	302	1.5%
c	296	1.5%
Other values (24)	3408	17.5%

Off_abbrev
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	94.9 KiB

0	231
TAM	53
LAR	53
CIN	52
SFO	49
Other values (27)	1187

Length

Max length	3
Median length	3
Mean length	2.715692308
Min length	1

Characters and Unicode

Total characters	4413
Distinct characters	25
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CHI
2nd row	GNB
3rd row	CAR
4th row	LAR
5th row	TEN

Common Values

Value	Count	Frequency (%)
0	231	14.2%
TAM	53	3.3%
LAR	53	3.3%
CIN	52	3.2%
SFO	49	3.0%
KAN	49	3.0%
BAL	48	3.0%
LVR	48	3.0%
NWE	48	3.0%
BUF	48	3.0%
Other values (22)	946	58.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	231	14.2%
lar	53	3.3%
tam	53	3.3%
cin	52	3.2%
sfo	49	3.0%
kan	49	3.0%
bal	48	3.0%
lvr	48	3.0%
buf	48	3.0%
nwe	48	3.0%
Other values (22)	946	58.2%

Most occurring characters

Value	Count	Frequency (%)
A	592	13.4%
N	486	11.0%
L	323	7.3%
I	318	7.2%
E	260	5.9%
R	235	5.3%
0	231	5.2%
T	230	5.2%
C	223	5.1%
D	176	4.0%
Other values (15)	1339	30.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4182	94.8%
Decimal Number	231	5.2%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	592	14.2%
N	486	11.6%
L	323	7.7%
I	318	7.6%
E	260	6.2%
R	235	5.6%
T	230	5.5%
C	223	5.3%
D	176	4.2%
O	138	3.3%
Other values (14)	1201	28.7%

Decimal Number

Value	Count	Frequency (%)
0	231	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4182	94.8%
Common	231	5.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	592	14.2%
N	486	11.6%
L	323	7.7%
I	318	7.6%
E	260	6.2%
R	235	5.6%
T	230	5.5%
C	223	5.3%
D	176	4.2%
O	138	3.3%
Other values (14)	1201	28.7%

Common

Value	Count	Frequency (%)
0	231	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4413	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	592	13.4%
N	486	11.0%
L	323	7.3%
I	318	7.2%
E	260	5.9%
R	235	5.3%
0	231	5.2%
T	230	5.2%
C	223	5.1%
D	176	4.0%
Other values (15)	1339	30.3%

Def_abbrev
Categorical

HIGH CORRELATION

Distinct	33
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	94.9 KiB

0	231
TAM	52
LAR	48
HOU	47
KAN	47
Other values (28)	1200

Length

Max length	3
Median length	3
Mean length	2.715692308
Min length	1

Characters and Unicode

Total characters	4413
Distinct characters	25
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	GNB
2nd row	CHI
3rd row	LAR
4th row	CAR
5th row	CLE

Common Values

Value	Count	Frequency (%)
0	231	14.2%
TAM	52	3.2%
LAR	48	3.0%
HOU	47	2.9%
KAN	47	2.9%
GNB	46	2.8%
MIN	46	2.8%
CIN	46	2.8%
SFO	46	2.8%
JAX	45	2.8%
Other values (23)	971	59.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	231	14.2%
tam	52	3.2%
lar	48	3.0%
hou	47	2.9%
kan	47	2.9%
gnb	46	2.8%
min	46	2.8%
cin	46	2.8%
sfo	46	2.8%
jax	45	2.8%
Other values (23)	971	59.8%

Most occurring characters

Value	Count	Frequency (%)
A	567	12.8%
N	481	10.9%
I	355	8.0%
L	299	6.8%
E	253	5.7%
0	231	5.2%
T	221	5.0%
R	220	5.0%
C	217	4.9%
D	163	3.7%
Other values (15)	1406	31.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4182	94.8%
Decimal Number	231	5.2%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	567	13.6%
N	481	11.5%
I	355	8.5%
L	299	7.1%
E	253	6.0%
T	221	5.3%
R	220	5.3%
C	217	5.2%
D	163	3.9%
M	143	3.4%
Other values (14)	1263	30.2%

Decimal Number

Value	Count	Frequency (%)
0	231	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4182	94.8%
Common	231	5.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	567	13.6%
N	481	11.5%
I	355	8.5%
L	299	7.1%
E	253	6.0%
T	221	5.3%
R	220	5.3%
C	217	5.2%
D	163	3.9%
M	143	3.4%
Other values (14)	1263	30.2%

Common

Value	Count	Frequency (%)
0	231	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4413	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	567	12.8%
N	481	10.9%
I	355	8.0%
L	299	6.8%
E	253	5.7%
0	231	5.2%
T	221	5.0%
R	220	5.0%
C	217	4.9%
D	163	3.7%
Other values (15)	1406	31.9%

fga
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.861538462

Minimum	0
Maximum	8
Zeros	231
Zeros (%)	14.2%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	2
Q3	3
95-th percentile	4
Maximum	8
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.281222417
Coefficient of variation (CV)	0.6882599763
Kurtosis	0.2141970194
Mean	1.861538462
Median Absolute Deviation (MAD)	1
Skewness	0.5378139105
Sum	3025
Variance	1.641530883
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
1	473	29.1%
2	440	27.1%
3	299	18.4%
0	231	14.2%
4	147	9.0%
5	28	1.7%
6	4	0.2%
8	2	0.1%
7	1	0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	231	14.2%
1	473	29.1%
2	440	27.1%
3	299	18.4%
4	147	9.0%
5	28	1.7%
6	4	0.2%
7	1	0.1%
8	2	0.1%

Value	Count	Frequency (%)
8	2	0.1%
7	1	0.1%
6	4	0.2%
5	28	1.7%
4	147	9.0%
3	299	18.4%
2	440	27.1%
1	473	29.1%
0	231	14.2%

fgm
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.604307692

Minimum	0
Maximum	7
Zeros	285
Zeros (%)	17.5%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	2
95-th percentile	4
Maximum	7
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.173540873
Coefficient of variation (CV)	0.7314936398
Kurtosis	0.08298606242
Mean	1.604307692
Median Absolute Deviation (MAD)	1
Skewness	0.5861799492
Sum	2607
Variance	1.377198181
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
1	557	34.3%
2	427	26.3%
0	285	17.5%
3	249	15.3%
4	91	5.6%
5	12	0.7%
6	3	0.2%
7	1	0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	285	17.5%
1	557	34.3%
2	427	26.3%
3	249	15.3%
4	91	5.6%
5	12	0.7%
6	3	0.2%
7	1	0.1%

Value	Count	Frequency (%)
7	1	0.1%
6	3	0.2%
5	12	0.7%
4	91	5.6%
3	249	15.3%
2	427	26.3%
1	557	34.3%
0	285	17.5%

xpa
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.445538462

Minimum	0
Maximum	8
Zeros	143
Zeros (%)	8.8%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	2
Q3	3
95-th percentile	5
Maximum	8
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.488343492
Coefficient of variation (CV)	0.6085954139
Kurtosis	0.006124483226
Mean	2.445538462
Median Absolute Deviation (MAD)	1
Skewness	0.4289574424
Sum	3974
Variance	2.215166351
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
2	422	26.0%
3	369	22.7%
1	314	19.3%
4	233	14.3%
0	143	8.8%
5	103	6.3%
6	28	1.7%
7	10	0.6%
8	3	0.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	143	8.8%
1	314	19.3%
2	422	26.0%
3	369	22.7%
4	233	14.3%
5	103	6.3%
6	28	1.7%
7	10	0.6%
8	3	0.2%

Value	Count	Frequency (%)
8	3	0.2%
7	10	0.6%
6	28	1.7%
5	103	6.3%
4	233	14.3%
3	369	22.7%
2	422	26.0%
1	314	19.3%
0	143	8.8%

xpm
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.286153846

Minimum	0
Maximum	8
Zeros	178
Zeros (%)	11.0%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	2
Q3	3
95-th percentile	5
Maximum	8
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.474315918
Coefficient of variation (CV)	0.6448891971
Kurtosis	-0.07748183724
Mean	2.286153846
Median Absolute Deviation (MAD)	1
Skewness	0.4468409697
Sum	3715
Variance	2.173607427
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
2	415	25.5%
1	353	21.7%
3	346	21.3%
4	214	13.2%
0	178	11.0%
5	85	5.2%
6	28	1.7%
8	3	0.2%
7	3	0.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	178	11.0%
1	353	21.7%
2	415	25.5%
3	346	21.3%
4	214	13.2%
5	85	5.2%
6	28	1.7%
7	3	0.2%
8	3	0.2%

Value	Count	Frequency (%)
8	3	0.2%
7	3	0.2%
6	28	1.7%
5	85	5.2%
4	214	13.2%
3	346	21.3%
2	415	25.5%
1	353	21.7%
0	178	11.0%

fga_0_39
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	7
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9224615385

Minimum	0
Maximum	6
Zeros	649
Zeros (%)	39.9%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	3
Maximum	6
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9675238041
Coefficient of variation (CV)	1.048850021
Kurtosis	1.1717699
Mean	0.9224615385
Median Absolute Deviation (MAD)	1
Skewness	1.070343411
Sum	1499
Variance	0.9361023115
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	649	39.9%
1	594	36.6%
2	273	16.8%
3	82	5.0%
4	23	1.4%
5	3	0.2%
6	1	0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	649	39.9%
1	594	36.6%
2	273	16.8%
3	82	5.0%
4	23	1.4%
5	3	0.2%
6	1	0.1%

Value	Count	Frequency (%)
6	1	0.1%
5	3	0.2%
4	23	1.4%
3	82	5.0%
2	273	16.8%
1	594	36.6%
0	649	39.9%

fgm_0_39
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.8750769231

Minimum	0
Maximum	5
Zeros	678
Zeros (%)	41.7%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	1
95-th percentile	3
Maximum	5
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.931668023
Coefficient of variation (CV)	1.064669857
Kurtosis	0.8034670667
Mean	0.8750769231
Median Absolute Deviation (MAD)	1
Skewness	1.014299913
Sum	1422
Variance	0.868005305
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	678	41.7%
1	589	36.2%
2	263	16.2%
3	75	4.6%
4	18	1.1%
5	2	0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	678	41.7%
1	589	36.2%
2	263	16.2%
3	75	4.6%
4	18	1.1%
5	2	0.1%

Value	Count	Frequency (%)
5	2	0.1%
4	18	1.1%
3	75	4.6%
2	263	16.2%
1	589	36.2%
0	678	41.7%

fga_40_49
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	92.2 KiB

0	932
1	519
2	144
3	27
4	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1625
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	2
5th row	0

Common Values

Value	Count	Frequency (%)
0	932	57.4%
1	519	31.9%
2	144	8.9%
3	27	1.7%
4	3	0.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	932	57.4%
1	519	31.9%
2	144	8.9%
3	27	1.7%
4	3	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	932	57.4%
1	519	31.9%
2	144	8.9%
3	27	1.7%
4	3	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1625	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	932	57.4%
1	519	31.9%
2	144	8.9%
3	27	1.7%
4	3	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	1625	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	932	57.4%
1	519	31.9%
2	144	8.9%
3	27	1.7%
4	3	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1625	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	932	57.4%
1	519	31.9%
2	144	8.9%
3	27	1.7%
4	3	0.2%

fgm_40_49
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	92.2 KiB

0	1063
1	448
2	98
3	16

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1625
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	1063	65.4%
1	448	27.6%
2	98	6.0%
3	16	1.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	1063	65.4%
1	448	27.6%
2	98	6.0%
3	16	1.0%

Most occurring characters

Value	Count	Frequency (%)
0	1063	65.4%
1	448	27.6%
2	98	6.0%
3	16	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1625	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1063	65.4%
1	448	27.6%
2	98	6.0%
3	16	1.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1625	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1063	65.4%
1	448	27.6%
2	98	6.0%
3	16	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1625	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1063	65.4%
1	448	27.6%
2	98	6.0%
3	16	1.0%

fga_50
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	92.2 KiB

0	1235
1	319
2	66
3	5

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1625
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	2
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	1235	76.0%
1	319	19.6%
2	66	4.1%
3	5	0.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	1235	76.0%
1	319	19.6%
2	66	4.1%
3	5	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	1235	76.0%
1	319	19.6%
2	66	4.1%
3	5	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1625	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1235	76.0%
1	319	19.6%
2	66	4.1%
3	5	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	1625	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1235	76.0%
1	319	19.6%
2	66	4.1%
3	5	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1625	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1235	76.0%
1	319	19.6%
2	66	4.1%
3	5	0.3%

fgm_50
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	92.2 KiB

0	1366
1	226
2	30
3	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1625
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	1366	84.1%
1	226	13.9%
2	30	1.8%
3	3	0.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	1366	84.1%
1	226	13.9%
2	30	1.8%
3	3	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	1366	84.1%
1	226	13.9%
2	30	1.8%
3	3	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1625	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1366	84.1%
1	226	13.9%
2	30	1.8%
3	3	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	1625	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1366	84.1%
1	226	13.9%
2	30	1.8%
3	3	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1625	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1366	84.1%
1	226	13.9%
2	30	1.8%
3	3	0.2%

player
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct	66
Distinct (%)	4.1%
Missing	0
Missing (%)	0.0%
Memory size	110.3 KiB

Harrison Butker	56
Mason Crosby	53
Justin Tucker	52
Jason Myers	51
Dustin Hopkins	50
Other values (61)	1363

Length

Max length	19
Median length	16
Mean length	12.45476923
Min length	7

Characters and Unicode

Total characters	20239
Distinct characters	47
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	0.6%

Sample

1st row	Eddy Pineiro
2nd row	Mason Crosby
3rd row	Joey Slye
4th row	Greg Zuerlein
5th row	Cairo Santos

Common Values

Value	Count	Frequency (%)
Harrison Butker	56	3.4%
Mason Crosby	53	3.3%
Justin Tucker	52	3.2%
Jason Myers	51	3.1%
Dustin Hopkins	50	3.1%
Jake Elliott	50	3.1%
Matt Prater	50	3.1%
Daniel Carlson	50	3.1%
Chris Boswell	48	3.0%
Greg Zuerlein	48	3.0%
Other values (56)	1117	68.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
matt	112	3.4%
jason	98	3.0%
greg	70	2.2%
harrison	56	1.7%
butker	56	1.7%
mason	53	1.6%
crosby	53	1.6%
elliott	53	1.6%
justin	52	1.6%
tucker	52	1.6%
Other values (109)	2595	79.8%

Most occurring characters

Value	Count	Frequency (%)
a	1767	8.7%
	1625	8.0%
o	1412	7.0%
n	1392	6.9%
e	1381	6.8%
r	1202	5.9%
i	1197	5.9%
s	1116	5.5%
l	925	4.6%
t	883	4.4%
Other values (37)	7339	36.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	15220	75.2%
Uppercase Letter	3349	16.5%
Space Separator	1625	8.0%
Other Punctuation	45	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1767	11.6%
o	1412	9.3%
n	1392	9.1%
e	1381	9.1%
r	1202	7.9%
i	1197	7.9%
s	1116	7.3%
l	925	6.1%
t	883	5.8%
u	610	4.0%
Other values (14)	3335	21.9%

Uppercase Letter

Value	Count	Frequency (%)
M	445	13.3%
B	366	10.9%
J	298	8.9%
S	289	8.6%
G	289	8.6%
C	250	7.5%
R	197	5.9%
D	134	4.0%
H	128	3.8%
P	119	3.6%
Other values (11)	834	24.9%

Space Separator

Value	Count	Frequency (%)
	1625	100.0%

Other Punctuation

Value	Count	Frequency (%)
'	45	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	18569	91.7%
Common	1670	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1767	9.5%
o	1412	7.6%
n	1392	7.5%
e	1381	7.4%
r	1202	6.5%
i	1197	6.4%
s	1116	6.0%
l	925	5.0%
t	883	4.8%
u	610	3.3%
Other values (35)	6684	36.0%

Common

Value	Count	Frequency (%)
	1625	97.3%
'	45	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	20239	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1767	8.7%
	1625	8.0%
o	1412	7.0%
n	1392	6.9%
e	1381	6.8%
r	1202	5.9%
i	1197	5.9%
s	1116	5.5%
l	925	4.6%
t	883	4.4%
Other values (37)	7339	36.3%

Total_DKP
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	26
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.522461538

Minimum	0
Maximum	25
Zeros	29
Zeros (%)	1.8%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	4
median	7
Q3	10
95-th percentile	15
Maximum	25
Range	25
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.359282474
Coefficient of variation (CV)	0.5795021287
Kurtosis	-0.005171211841
Mean	7.522461538
Median Absolute Deviation (MAD)	3
Skewness	0.5132432102
Sum	12224
Variance	19.00334369
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
6	140	8.6%
4	140	8.6%
7	140	8.6%
5	132	8.1%
9	130	8.0%
10	121	7.4%
3	112	6.9%
8	110	6.8%
2	92	5.7%
12	88	5.4%
Other values (16)	420	25.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	29	1.8%
1	85	5.2%
2	92	5.7%
3	112	6.9%
4	140	8.6%
5	132	8.1%
6	140	8.6%
7	140	8.6%
8	110	6.8%
9	130	8.0%

Value	Count	Frequency (%)
25	1	0.1%
24	2	0.1%
23	1	0.1%
22	2	0.1%
21	4	0.2%
20	3	0.2%
19	2	0.1%
18	10	0.6%
17	15	0.9%
16	34	2.1%

Total_FDP
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	26
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.522461538

Minimum	0
Maximum	25
Zeros	29
Zeros (%)	1.8%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	4
median	7
Q3	10
95-th percentile	15
Maximum	25
Range	25
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.359282474
Coefficient of variation (CV)	0.5795021287
Kurtosis	-0.005171211841
Mean	7.522461538
Median Absolute Deviation (MAD)	3
Skewness	0.5132432102
Sum	12224
Variance	19.00334369
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
6	140	8.6%
4	140	8.6%
7	140	8.6%
5	132	8.1%
9	130	8.0%
10	121	7.4%
3	112	6.9%
8	110	6.8%
2	92	5.7%
12	88	5.4%
Other values (16)	420	25.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	29	1.8%
1	85	5.2%
2	92	5.7%
3	112	6.9%
4	140	8.6%
5	132	8.1%
6	140	8.6%
7	140	8.6%
8	110	6.8%
9	130	8.0%

Value	Count	Frequency (%)
25	1	0.1%
24	2	0.1%
23	1	0.1%
22	2	0.1%
21	4	0.2%
20	3	0.2%
19	2	0.1%
18	10	0.6%
17	15	0.9%
16	34	2.1%

Total_SDP
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	26
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.522461538

Minimum	0
Maximum	25
Zeros	29
Zeros (%)	1.8%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	4
median	7
Q3	10
95-th percentile	15
Maximum	25
Range	25
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.359282474
Coefficient of variation (CV)	0.5795021287
Kurtosis	-0.005171211841
Mean	7.522461538
Median Absolute Deviation (MAD)	3
Skewness	0.5132432102
Sum	12224
Variance	19.00334369
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
6	140	8.6%
4	140	8.6%
7	140	8.6%
5	132	8.1%
9	130	8.0%
10	121	7.4%
3	112	6.9%
8	110	6.8%
2	92	5.7%
12	88	5.4%
Other values (16)	420	25.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	29	1.8%
1	85	5.2%
2	92	5.7%
3	112	6.9%
4	140	8.6%
5	132	8.1%
6	140	8.6%
7	140	8.6%
8	110	6.8%
9	130	8.0%

Value	Count	Frequency (%)
25	1	0.1%
24	2	0.1%
23	1	0.1%
22	2	0.1%
21	4	0.2%
20	3	0.2%
19	2	0.1%
18	10	0.6%
17	15	0.9%
16	34	2.1%

vis_team
Categorical

HIGH CORRELATION
UNIFORM

Distinct	32
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	95.3 KiB

TAM	58
LAR	58
SFO	56
TEN	53
CLE	53
Other values (27)	1347

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	4875
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	GNB
2nd row	GNB
3rd row	LAR
4th row	LAR
5th row	TEN

Common Values

Value	Count	Frequency (%)
TAM	58	3.6%
LAR	58	3.6%
SFO	56	3.4%
TEN	53	3.3%
CLE	53	3.3%
SEA	53	3.3%
MIN	53	3.3%
CIN	52	3.2%
ARI	52	3.2%
CHI	52	3.2%
Other values (22)	1085	66.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
tam	58	3.6%
lar	58	3.6%
sfo	56	3.4%
ten	53	3.3%
cle	53	3.3%
sea	53	3.3%
min	53	3.3%
cin	52	3.2%
chi	52	3.2%
phi	52	3.2%
Other values (22)	1085	66.8%

Most occurring characters

Value	Count	Frequency (%)
A	662	13.6%
N	547	11.2%
I	409	8.4%
L	359	7.4%
E	304	6.2%
T	260	5.3%
R	259	5.3%
C	254	5.2%
D	196	4.0%
M	160	3.3%
Other values (14)	1465	30.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4875	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	662	13.6%
N	547	11.2%
I	409	8.4%
L	359	7.4%
E	304	6.2%
T	260	5.3%
R	259	5.3%
C	254	5.2%
D	196	4.0%
M	160	3.3%
Other values (14)	1465	30.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4875	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	662	13.6%
N	547	11.2%
I	409	8.4%
L	359	7.4%
E	304	6.2%
T	260	5.3%
R	259	5.3%
C	254	5.2%
D	196	4.0%
M	160	3.3%
Other values (14)	1465	30.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4875	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	662	13.6%
N	547	11.2%
I	409	8.4%
L	359	7.4%
E	304	6.2%
T	260	5.3%
R	259	5.3%
C	254	5.2%
D	196	4.0%
M	160	3.3%
Other values (14)	1465	30.1%

home_team
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct	32
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	95.3 KiB

KAN	66
GNB	55
BUF	54
CIN	54
TAM	53
Other values (27)	1343

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	4875
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CHI
2nd row	CHI
3rd row	CAR
4th row	CAR
5th row	CLE

Common Values

Value	Count	Frequency (%)
KAN	66	4.1%
GNB	55	3.4%
BUF	54	3.3%
CIN	54	3.3%
TAM	53	3.3%
NOR	53	3.3%
TEN	53	3.3%
PIT	52	3.2%
LAR	52	3.2%
BAL	52	3.2%
Other values (22)	1081	66.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kan	66	4.1%
gnb	55	3.4%
buf	54	3.3%
cin	54	3.3%
tam	53	3.3%
nor	53	3.3%
ten	53	3.3%
pit	52	3.2%
bal	52	3.2%
nwe	52	3.2%
Other values (22)	1081	66.5%

Most occurring characters

Value	Count	Frequency (%)
A	663	13.6%
N	576	11.8%
I	395	8.1%
L	351	7.2%
E	301	6.2%
T	254	5.2%
R	250	5.1%
C	248	5.1%
D	195	4.0%
B	161	3.3%
Other values (14)	1481	30.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4875	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	663	13.6%
N	576	11.8%
I	395	8.1%
L	351	7.2%
E	301	6.2%
T	254	5.2%
R	250	5.1%
C	248	5.1%
D	195	4.0%
B	161	3.3%
Other values (14)	1481	30.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4875	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	663	13.6%
N	576	11.8%
I	395	8.1%
L	351	7.2%
E	301	6.2%
T	254	5.2%
R	250	5.1%
C	248	5.1%
D	195	4.0%
B	161	3.3%
Other values (14)	1481	30.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4875	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	663	13.6%
N	576	11.8%
I	395	8.1%
L	351	7.2%
E	301	6.2%
T	254	5.2%
R	250	5.1%
C	248	5.1%
D	195	4.0%
B	161	3.3%
Other values (14)	1481	30.4%

vis_score
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	50
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.25292308

Minimum	0
Maximum	59
Zeros	9
Zeros (%)	0.6%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	7
Q1	16
median	23
Q3	30
95-th percentile	41
Maximum	59
Range	59
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	10.09478017
Coefficient of variation (CV)	0.4341295127
Kurtosis	-0.234750463
Mean	23.25292308
Median Absolute Deviation (MAD)	7
Skewness	0.116837092
Sum	37786
Variance	101.9045866
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
17	107	6.6%
27	92	5.7%
20	92	5.7%
31	90	5.5%
24	80	4.9%
30	76	4.7%
16	67	4.1%
23	66	4.1%
21	64	3.9%
10	62	3.8%
Other values (40)	829	51.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	9	0.6%
3	40	2.5%
5	2	0.1%
6	19	1.2%
7	38	2.3%
8	1	0.1%
9	42	2.6%
10	62	3.8%
11	12	0.7%
12	15	0.9%

Value	Count	Frequency (%)
59	2	0.1%
55	2	0.1%
51	2	0.1%
49	4	0.2%
48	6	0.4%
47	4	0.2%
46	2	0.1%
45	12	0.7%
44	4	0.2%
43	9	0.6%

home_score
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	50
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	23.94830769

Minimum	0
Maximum	56
Zeros	12
Zeros (%)	0.7%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	7
Q1	17
median	24
Q3	31
95-th percentile	41
Maximum	56
Range	56
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	10.05164184
Coefficient of variation (CV)	0.4197224274
Kurtosis	-0.05326707193
Mean	23.94830769
Median Absolute Deviation (MAD)	7
Skewness	0.2124142326
Sum	38916
Variance	101.0355036
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
24	112	6.9%
20	105	6.5%
17	103	6.3%
27	100	6.2%
23	71	4.4%
31	71	4.4%
13	70	4.3%
34	66	4.1%
16	65	4.0%
10	64	3.9%
Other values (40)	798	49.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	12	0.7%
3	22	1.4%
6	27	1.7%
7	22	1.4%
9	22	1.4%
10	64	3.9%
11	10	0.6%
12	12	0.7%
13	70	4.3%
14	28	1.7%

Value	Count	Frequency (%)
56	4	0.2%
54	2	0.1%
53	2	0.1%
52	2	0.1%
51	6	0.4%
50	2	0.1%
48	4	0.2%
47	6	0.4%
46	4	0.2%
45	9	0.6%

OT
Boolean

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.7 KiB

False	1537
True	88

Common Values
Category Frequency Plot

Value	Count	Frequency (%)
False	1537	94.6%
True	88	5.4%

Roof
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	106.4 KiB

outdoors	1123
dome	252
retractable roof (closed)	218
retractable roof (open)	32

Length

Max length	25
Median length	8
Mean length	9.955692308
Min length	4

Characters and Unicode

Total characters	16178
Distinct characters	18
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	outdoors
2nd row	outdoors
3rd row	outdoors
4th row	outdoors
5th row	outdoors

Common Values

Value	Count	Frequency (%)
outdoors	1123	69.1%
dome	252	15.5%
retractable roof (closed)	218	13.4%
retractable roof (open)	32	2.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
outdoors	1123	52.8%
dome	252	11.9%
retractable	250	11.8%
roof	250	11.8%
closed	218	10.3%
open	32	1.5%

Most occurring characters

Value	Count	Frequency (%)
o	4371	27.0%
r	1873	11.6%
t	1623	10.0%
d	1593	9.8%
s	1341	8.3%
u	1123	6.9%
e	1002	6.2%
	500	3.1%
a	500	3.1%
l	468	2.9%
Other values (8)	1784	11.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	15178	93.8%
Space Separator	500	3.1%
Open Punctuation	250	1.5%
Close Punctuation	250	1.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	4371	28.8%
r	1873	12.3%
t	1623	10.7%
d	1593	10.5%
s	1341	8.8%
u	1123	7.4%
e	1002	6.6%
a	500	3.3%
l	468	3.1%
c	468	3.1%
Other values (5)	816	5.4%

Space Separator

Value	Count	Frequency (%)
	500	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	250	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	250	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	15178	93.8%
Common	1000	6.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	4371	28.8%
r	1873	12.3%
t	1623	10.7%
d	1593	10.5%
s	1341	8.8%
u	1123	7.4%
e	1002	6.6%
a	500	3.3%
l	468	3.1%
c	468	3.1%
Other values (5)	816	5.4%

Common

Value	Count	Frequency (%)
	500	50.0%
(	250	25.0%
)	250	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16178	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	4371	27.0%
r	1873	11.6%
t	1623	10.0%
d	1593	9.8%
s	1341	8.3%
u	1123	6.9%
e	1002	6.2%
	500	3.1%
a	500	3.1%
l	468	2.9%
Other values (8)	1784	11.0%

Surface
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	8
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	101.5 KiB

grass	737
grass	248
fieldturf	186
fieldturf	176
astroturf	111
Other values (3)	167

Length

Max length	10
Median length	9
Mean length	6.864
Min length	5

Characters and Unicode

Total characters	11154
Distinct characters	17
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	grass
2nd row	grass
3rd row	grass
4th row	grass
5th row	grass

Common Values

Value	Count	Frequency (%)
grass	737	45.4%
grass	248	15.3%
fieldturf	186	11.4%
fieldturf	176	10.8%
astroturf	111	6.8%
matrixturf	89	5.5%
sportturf	60	3.7%
a_turf	18	1.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
grass	985	60.6%
fieldturf	362	22.3%
astroturf	111	6.8%
matrixturf	89	5.5%
sportturf	60	3.7%
a_turf	18	1.1%

Most occurring characters

Value	Count	Frequency (%)
s	2141	19.2%
r	1885	16.9%
a	1203	10.8%
f	1002	9.0%
g	985	8.8%
t	900	8.1%
u	640	5.7%
i	451	4.0%
	434	3.9%
l	362	3.2%
Other values (7)	1151	10.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10702	95.9%
Space Separator	434	3.9%
Connector Punctuation	18	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	2141	20.0%
r	1885	17.6%
a	1203	11.2%
f	1002	9.4%
g	985	9.2%
t	900	8.4%
u	640	6.0%
i	451	4.2%
l	362	3.4%
d	362	3.4%
Other values (5)	771	7.2%

Space Separator

Value	Count	Frequency (%)
	434	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	18	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10702	95.9%
Common	452	4.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	2141	20.0%
r	1885	17.6%
a	1203	11.2%
f	1002	9.4%
g	985	9.2%
t	900	8.4%
u	640	6.0%
i	451	4.2%
l	362	3.4%
d	362	3.4%
Other values (5)	771	7.2%

Common

Value	Count	Frequency (%)
	434	96.0%
_	18	4.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11154	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
s	2141	19.2%
r	1885	16.9%
a	1203	10.8%
f	1002	9.0%
g	985	8.8%
t	900	8.1%
u	640	5.7%
i	451	4.0%
	434	3.9%
l	362	3.2%
Other values (7)	1151	10.3%

Temperature
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	73
Distinct (%)	4.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	62.78584615

Minimum	7
Maximum	93
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	7
5-th percentile	35
Q1	52
median	72
Q3	72
95-th percentile	82
Maximum	93
Range	86
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	15.27771395
Coefficient of variation (CV)	0.2433305415
Kurtosis	-0.1185534416
Mean	62.78584615
Median Absolute Deviation (MAD)	8
Skewness	-0.7708927782
Sum	102027
Variance	233.4085434
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
72	550	33.8%
48	34	2.1%
52	32	2.0%
54	30	1.8%
81	29	1.8%
43	28	1.7%
76	28	1.7%
59	28	1.7%
46	26	1.6%
64	26	1.6%
Other values (63)	814	50.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
7	2	0.1%
11	4	0.2%
14	2	0.1%
15	2	0.1%
23	2	0.1%
24	2	0.1%
25	6	0.4%
26	2	0.1%
28	2	0.1%
29	2	0.1%

Value	Count	Frequency (%)
93	4	0.2%
91	4	0.2%
90	2	0.1%
89	1	0.1%
88	8	0.5%
87	13	0.8%
86	8	0.5%
85	18	1.1%
84	7	0.4%
83	14	0.9%

Humidity
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	85
Distinct (%)	5.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	55.72061538

Minimum	0
Maximum	100
Zeros	2
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	35.2
Q1	45
median	48
Q3	68
95-th percentile	88
Maximum	100
Range	100
Interquartile range (IQR)	23

Descriptive statistics

Standard deviation	16.97849189
Coefficient of variation (CV)	0.3047075444
Kurtosis	-0.004525211045
Mean	55.72061538
Median Absolute Deviation (MAD)	8
Skewness	0.4281067826
Sum	90546
Variance	288.2691868
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
45	544	33.5%
56	34	2.1%
46	30	1.8%
52	29	1.8%
60	28	1.7%
66	28	1.7%
58	27	1.7%
67	25	1.5%
59	24	1.5%
57	24	1.5%
Other values (75)	832	51.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	0.1%
7	2	0.1%
8	2	0.1%
9	3	0.2%
10	2	0.1%
11	2	0.1%
12	2	0.1%
13	1	0.1%
14	6	0.4%
19	4	0.2%

Value	Count	Frequency (%)
100	4	0.2%
99	4	0.2%
97	2	0.1%
95	2	0.1%
94	4	0.2%
93	13	0.8%
92	10	0.6%
91	14	0.9%
90	12	0.7%
89	11	0.7%

Wind_Speed
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	28
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.851692308

Minimum	0
Maximum	35
Zeros	589
Zeros (%)	36.2%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	5
Q3	10
95-th percentile	17
Maximum	35
Range	35
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.002424482
Coefficient of variation (CV)	1.025758732
Kurtosis	0.4715231197
Mean	5.851692308
Median Absolute Deviation (MAD)	5
Skewness	0.9059521431
Sum	9509
Variance	36.02909966
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
0	589	36.2%
8	108	6.6%
7	93	5.7%
4	87	5.4%
6	85	5.2%
5	73	4.5%
9	68	4.2%
10	64	3.9%
12	61	3.8%
11	59	3.6%
Other values (18)	338	20.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	589	36.2%
1	24	1.5%
2	32	2.0%
3	46	2.8%
4	87	5.4%
5	73	4.5%
6	85	5.2%
7	93	5.7%
8	108	6.6%
9	68	4.2%

Value	Count	Frequency (%)
35	2	0.1%
27	2	0.1%
25	2	0.1%
24	4	0.2%
23	8	0.5%
22	8	0.5%
21	6	0.4%
20	6	0.4%
19	24	1.5%
18	12	0.7%

Vegas_Line
Real number (ℝ)

Distinct	39
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-5.660923077

Minimum	-22
Maximum	0
Zeros	4
Zeros (%)	0.2%
Negative	1621
Negative (%)	99.8%
Memory size	12.8 KiB

Quantile statistics

Minimum	-22
5-th percentile	-13
Q1	-7.5
median	-4.5
Q3	-3
95-th percentile	-1
Maximum	0
Range	22
Interquartile range (IQR)	4.5

Descriptive statistics

Standard deviation	3.676887322
Coefficient of variation (CV)	-0.6495208064
Kurtosis	1.369975557
Mean	-5.660923077
Median Absolute Deviation (MAD)	2
Skewness	-1.17694802
Sum	-9199
Variance	13.51950038
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=39)

Value	Count	Frequency (%)
-3	215	13.2%
-3.5	163	10.0%
-7	114	7.0%
-2.5	112	6.9%
-1	100	6.2%
-4	89	5.5%
-7.5	86	5.3%
-6.5	78	4.8%
-6	72	4.4%
-5.5	70	4.3%
Other values (29)	526	32.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-22	2	0.1%
-20.5	2	0.1%
-20	2	0.1%
-18	3	0.2%
-17.5	5	0.3%
-17	6	0.4%
-16.5	12	0.7%
-16	2	0.1%
-15.5	4	0.2%
-15	4	0.2%

Value	Count	Frequency (%)
0	4	0.2%
-1	100	6.2%
-1.5	48	3.0%
-2	40	2.5%
-2.5	112	6.9%
-3	215	13.2%
-3.5	163	10.0%
-4	89	5.5%
-4.5	46	2.8%
-5	52	3.2%

Vegas_Favorite
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	33
Distinct (%)	2.0%
Missing	4
Missing (%)	0.2%
Memory size	95.3 KiB

KAN	104
LAR	86
GNB	83
TAM	81
BAL	77
Other values (28)	1190

Length

Max length	19
Median length	3
Mean length	3.059222702
Min length	3

Characters and Unicode

Total characters	4959
Distinct characters	34
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CHI
2nd row	CHI
3rd row	LAR
4th row	LAR
5th row	CLE

Common Values

Value	Count	Frequency (%)
KAN	104	6.4%
LAR	86	5.3%
GNB	83	5.1%
TAM	81	5.0%
BAL	77	4.7%
NOR	72	4.4%
NWE	72	4.4%
DAL	71	4.4%
SFO	69	4.2%
SEA	68	4.2%
Other values (23)	838	51.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kan	104	6.4%
lar	86	5.3%
gnb	83	5.1%
tam	81	5.0%
bal	77	4.7%
nor	72	4.4%
nwe	72	4.4%
dal	71	4.3%
sfo	69	4.2%
sea	68	4.2%
Other values (25)	850	52.1%

Most occurring characters

Value	Count	Frequency (%)
A	718	14.5%
N	591	11.9%
L	425	8.6%
I	349	7.0%
E	312	6.3%
R	285	5.7%
T	240	4.8%
B	226	4.6%
C	220	4.4%
O	177	3.6%
Other values (24)	1416	28.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4875	98.3%
Lowercase Letter	60	1.2%
Space Separator	12	0.2%
Connector Punctuation	6	0.1%
Dash Punctuation	6	0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	718	14.7%
N	591	12.1%
L	425	8.7%
I	349	7.2%
E	312	6.4%
R	285	5.8%
T	240	4.9%
B	226	4.6%
C	220	4.5%
O	177	3.6%
Other values (14)	1332	27.3%

Lowercase Letter

Value	Count	Frequency (%)
a	12	20.0%
b	12	20.0%
e	12	20.0%
t	6	10.0%
v	6	10.0%
r	6	10.0%
m	6	10.0%

Space Separator

Value	Count	Frequency (%)
	12	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	6	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	6	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4935	99.5%
Common	24	0.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	718	14.5%
N	591	12.0%
L	425	8.6%
I	349	7.1%
E	312	6.3%
R	285	5.8%
T	240	4.9%
B	226	4.6%
C	220	4.5%
O	177	3.6%
Other values (21)	1392	28.2%

Common

Value	Count	Frequency (%)
	12	50.0%
_	6	25.0%
-	6	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4959	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	718	14.5%
N	591	11.9%
L	425	8.6%
I	349	7.0%
E	312	6.3%
R	285	5.7%
T	240	4.8%
B	226	4.6%
C	220	4.4%
O	177	3.6%
Other values (24)	1416	28.6%

Over_Under
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	44
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	46.61107692

Minimum	35
Maximum	58
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.8 KiB

Quantile statistics

Minimum	35
5-th percentile	40
Q1	43.5
median	46.5
Q3	49.5
95-th percentile	54.5
Maximum	58
Range	23
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.263539763
Coefficient of variation (CV)	0.09147052686
Kurtosis	-0.3061021445
Mean	46.61107692
Median Absolute Deviation (MAD)	3
Skewness	0.1249977772
Sum	75743
Variance	18.17777131
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=44)

Value	Count	Frequency (%)
44	94	5.8%
47	88	5.4%
48	78	4.8%
46	74	4.6%
46.5	73	4.5%
49	72	4.4%
45	71	4.4%
43	68	4.2%
44.5	65	4.0%
49.5	63	3.9%
Other values (34)	879	54.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
35	2	0.1%
36.5	8	0.5%
37	14	0.9%
37.5	12	0.7%
38	7	0.4%
38.5	6	0.4%
39	10	0.6%
39.5	18	1.1%
40	16	1.0%
40.5	14	0.9%

Value	Count	Frequency (%)
58	2	0.1%
57.5	2	0.1%
56.5	12	0.7%
56	4	0.2%
55.5	20	1.2%
55	22	1.4%
54.5	28	1.7%
54	16	1.0%
53.5	20	1.2%
53	12	0.7%

game_date
Categorical

HIGH CARDINALITY

Distinct	174
Distinct (%)	10.7%
Missing	0
Missing (%)	0.0%
Memory size	106.4 KiB

2021-01-03	32
2019-12-29	32
2022-01-02	30
2021-10-10	29
2020-09-27	28
Other values (169)	1474

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	16250
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	2019-09-05
2nd row	2019-09-05
3rd row	2019-09-08
4th row	2019-09-08
5th row	2019-09-08

Common Values

Value	Count	Frequency (%)
2021-01-03	32	2.0%
2019-12-29	32	2.0%
2022-01-02	30	1.8%
2021-10-10	29	1.8%
2020-09-27	28	1.7%
2019-12-15	28	1.7%
2020-09-20	28	1.7%
2022-01-09	28	1.7%
2019-12-08	28	1.7%
2019-09-22	28	1.7%
Other values (164)	1334	82.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2021-01-03	32	2.0%
2019-12-29	32	2.0%
2022-01-02	30	1.8%
2021-10-10	29	1.8%
2020-09-27	28	1.7%
2019-12-15	28	1.7%
2020-09-20	28	1.7%
2022-01-09	28	1.7%
2019-12-08	28	1.7%
2019-09-22	28	1.7%
Other values (164)	1334	82.1%

Most occurring characters

Value	Count	Frequency (%)
2	4006	24.7%
0	3605	22.2%
1	3402	20.9%
-	3250	20.0%
9	1013	6.2%
3	224	1.4%
7	176	1.1%
5	161	1.0%
8	154	0.9%
6	137	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	13000	80.0%
Dash Punctuation	3250	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	4006	30.8%
0	3605	27.7%
1	3402	26.2%
9	1013	7.8%
3	224	1.7%
7	176	1.4%
5	161	1.2%
8	154	1.2%
6	137	1.1%
4	122	0.9%

Dash Punctuation

Value	Count	Frequency (%)
-	3250	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	16250	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	4006	24.7%
0	3605	22.2%
1	3402	20.9%
-	3250	20.0%
9	1013	6.2%
3	224	1.4%
7	176	1.1%
5	161	1.0%
8	154	0.9%
6	137	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16250	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	4006	24.7%
0	3605	22.2%
1	3402	20.9%
-	3250	20.0%
9	1013	6.2%
3	224	1.4%
7	176	1.1%
5	161	1.0%
8	154	0.9%
6	137	0.8%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	game_id	Off_abbrev	Def_abbrev	fga	fgm	xpa	xpm	fga_0_39	fgm_0_39	fga_40_49	fgm_40_49	fga_50	fgm_50	player	Total_DKP	Total_FDP	Total_SDP	vis_team	home_team	vis_score	home_score	OT	Roof	Surface	Temperature	Humidity	Wind_Speed	Vegas_Line	Vegas_Favorite	Over_Under	game_date
0	201909050chi	CHI	GNB	1	1	0	0	1	1	0	0	0	0	Eddy Pineiro	3	3	3	GNB	CHI	10	3	False	outdoors	grass	65	69	10	-3.5	CHI	47.0	2019-09-05
1	201909050chi	GNB	CHI	1	1	1	1	1	1	0	0	0	0	Mason Crosby	4	4	4	GNB	CHI	10	3	False	outdoors	grass	65	69	10	-3.5	CHI	47.0	2019-09-05
2	201909080car	CAR	LAR	3	2	3	3	0	0	1	1	2	1	Joey Slye	12	12	12	LAR	CAR	30	27	False	outdoors	grass	87	53	3	-1.5	LAR	49.5	2019-09-08
3	201909080car	LAR	CAR	4	3	3	3	1	1	2	1	1	1	Greg Zuerlein	15	15	15	LAR	CAR	30	27	False	outdoors	grass	87	53	3	-1.5	LAR	49.5	2019-09-08
4	201909080cle	TEN	CLE	2	2	5	5	1	1	0	0	1	1	Cairo Santos	13	13	13	TEN	CLE	43	13	False	outdoors	grass	71	55	10	-5.5	CLE	44.0	2019-09-08
5	201909080cle	0	0	0	0	2	1	0	0	0	0	0	0	Austin Seibert	1	1	1	TEN	CLE	43	13	False	outdoors	grass	71	55	10	-5.5	CLE	44.0	2019-09-08
6	201909080crd	ARI	DET	4	4	1	1	3	3	1	1	0	0	Zane Gonzalez	14	14	14	DET	ARI	27	27	True	retractable roof (closed)	grass	72	45	0	-2.5	DET	45.5	2019-09-08
7	201909080crd	DET	ARI	2	2	3	3	1	1	0	0	1	1	Matt Prater	11	11	11	DET	ARI	27	27	True	retractable roof (closed)	grass	72	45	0	-2.5	DET	45.5	2019-09-08
8	201909080dal	0	0	0	0	5	5	0	0	0	0	0	0	Brett Maher	5	5	5	NYG	DAL	17	35	False	retractable roof (closed)	fieldturf	72	45	0	-7.0	DAL	44.0	2019-09-08
9	201909080dal	NYG	DAL	1	1	2	2	1	1	0	0	0	0	Aldrick Rosas	5	5	5	NYG	DAL	17	35	False	retractable roof (closed)	fieldturf	72	45	0	-7.0	DAL	44.0	2019-09-08

Last rows

	game_id	Off_abbrev	Def_abbrev	fga	fgm	xpa	xpm	fga_0_39	fgm_0_39	fga_40_49	fgm_40_49	fga_50	fgm_50	player	Total_DKP	Total_FDP	Total_SDP	vis_team	home_team	vis_score	home_score	OT	Roof	Surface	Temperature	Humidity	Wind_Speed	Vegas_Line	Vegas_Favorite	Over_Under	game_date
1615	202201230kan	0	0	0	0	4	4	0	0	0	0	0	0	Tyler Bass	4	4	4	BUF	KAN	36	42	True	outdoors	grass	35	54	6	-2.0	KAN	54.5	2022-01-23
1616	202201230kan	KAN	BUF	4	3	4	3	2	2	1	1	1	0	Harrison Butker	13	13	13	BUF	KAN	36	42	True	outdoors	grass	35	54	6	-2.0	KAN	54.5	2022-01-23
1617	202201230tam	TAM	LAR	3	2	3	3	0	0	0	0	0	0	Ryan Succop	3	3	3	LAR	TAM	30	27	False	outdoors	grass	50	69	11	-3.0	TAM	48.0	2022-01-23
1618	202201230tam	LAR	TAM	4	3	3	3	3	3	1	0	0	0	Matt Gay	12	12	12	LAR	TAM	30	27	False	outdoors	grass	50	69	11	-3.0	TAM	48.0	2022-01-23
1619	202201300kan	CIN	KAN	4	4	1	1	3	3	0	0	1	1	Evan McPherson	15	15	15	CIN	KAN	27	24	True	outdoors	grass	41	41	4	-7.0	KAN	55.0	2022-01-30
1620	202201300kan	KAN	CIN	1	1	3	3	0	0	1	1	0	0	Harrison Butker	7	7	7	CIN	KAN	27	24	True	outdoors	grass	41	41	4	-7.0	KAN	55.0	2022-01-30
1621	202201300ram	LAR	SFO	3	2	2	2	1	1	1	1	1	0	Matt Gay	9	9	9	SFO	LAR	17	20	False	dome	matrixturf	72	45	0	-3.5	LAR	46.0	2022-01-30
1622	202201300ram	SFO	LAR	1	1	2	2	0	0	0	0	0	0	Robbie Gould	2	2	2	SFO	LAR	17	20	False	dome	matrixturf	72	45	0	-3.5	LAR	46.0	2022-01-30
1623	202202130cin	CIN	LAR	2	2	2	2	0	0	0	0	0	0	Evan McPherson	2	2	2	LAR	CIN	23	20	False	dome	matrixturf	72	45	0	-4.0	LAR	48.5	2022-02-13
1624	202202130cin	LAR	CIN	1	1	2	2	0	0	1	1	0	0	Matt Gay	6	6	6	LAR	CIN	23	20	False	dome	matrixturf	72	45	0	-4.0	LAR	48.5	2022-02-13

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common